Related papers: Distinguishing True Influence from Hyperprolificit…
The data of F1000 provide us with the unique opportunity to investigate the relationship between peers' ratings and bibliometric metrics on a broad and comprehensive data set with high-quality ratings. F1000 is a post-publication peer…
In recent years bibliometricians have paid increasing attention to research evaluation methodological problems, among these being the choice of the most appropriate indicators for evaluating quality of scientific publications, and thus for…
I compare several network-level measures of centrality to common measures of author reputation and influence (e.g. hindex, i10index), all taken over the data set of papers published in 2017 at major computer systems conferences and some…
Citation prediction of scholarly papers is of great significance in guiding funding allocations, recruitment decisions, and rewards. However, little is known about how citation patterns evolve over time. By exploring the inherent involution…
Evaluation of journals for quality is one of the dominant themes of bibliometrics since journals are the primary venue of vetting and distribution of scholarship. There are many criticisms of quantifying journal impact with bibliometrics…
Quantifying the interdisciplinarity of a research is a relevant problem in the evaluative bibliometrics. The concept of interdisciplinarity is ambiguous and multidimensional. Thus, different measures of interdisciplinarity have been propose…
This literature review identifies indicators that associate with higher impact or higher quality research from article text (e.g., titles, abstracts, lengths, cited references and readability) or metadata (e.g., the number of authors,…
The proliferation of surveys and review articles in academic journals has impacted citation metrics like impact factor and h-index, skewing evaluations of journal and researcher quality. This work investigates the implications of this…
Metrics based on percentile ranks (PRs) for measuring scholarly impact involves complex treatment because of various defects such as overvaluing or devaluing an object caused by percentile ranking schemes, ignoring precise citation…
Citation metrics are widely used to assess academic impact but suffer from social biases, including institutional prestige and journal visibility. Here we introduce rXiv Semantic Impact (XSI), a novel framework that predicts research impact…
The ACM A.M. Turing Award is commonly acknowledged as the highest distinction in the realm of computer science. Since 1960s, it has been awarded to computer scientists who made outstanding contributions. The significance of this award is…
Although bibliometrics has been a separate research field for many years, there is still no uniformity in the way bibliometric analyses are applied to individual researchers. Therefore, this study aims to set up proposals how to evaluate…
Heretofore, the only way to evaluate an author has been frequency-based citation metrics that assume citations to be of a neutral sentiment. However, considering the sentiment behind citations aids in a better understanding of the…
Deep learning has had a great impact on various fields of computer science by enabling data-driven representation learning in a decade. Because science and technology policy decisions for a nation can be made on the impact of each…
I propose the P-Index that genuinely constitutes a well-defined, compact author citation metric.
Using bibliometric data artificially generated through a model of citation dynamics calibrated on empirical data, we compare several indicators for the scientific impact of individual researchers. The use of such a controlled setup has the…
Science has become more collaborative over the past years, a phenomenon that is related to the increase in the number of authors per paper and the emergence of interdisciplinary works featuring specialists of different fields. In such a…
How much is the h-index of an editor of a well ranked journal improved due to citations which occur after his or her appointment? Scientific recognition within academia is widely measured nowadays by the number of citations or h-index. Our…
The use of quantitative indicators of scientific productivity seems now quite widespread for assessing researchers and research institutions. There is a general perception, however, that these indicators are not necessarily representative…
There are two principal data sources for collaborative filtering recommenders in scholarly digital libraries: usage data obtained from harvesting a large, distributed collection of Open URL web logs and citation data obtained from the…